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1 Econometrica, Vol. 72, No. 1 (January, 2004), WORMS: IDENTIFYING IMPACTS ON EDUCATION AND HEALTH IN THE PRESENCE OF TREATMENT EXTERNALITIES BY EDWARD MIGUEL AND MICHAEL KREMER 1 Intestinal helminths including hookworm, roundworm, whipworm, and schistosomiasis infect more than one-quarter of the world s population. Studies in which medical treatment is randomized at the individual level potentially doubly underestimate the benefits of treatment, missing externality benefits to the comparison group from reduced disease transmission, and therefore also underestimating benefits for the treatment group. We evaluate a Kenyan project in which school-based mass treatment with deworming drugs was randomly phased into schools, rather than to individuals, allowing estimation of overall program effects. The program reduced school absenteeism in treatment schools by one-quarter, and was far cheaper than alternative ways of boosting school participation. Deworming substantially improved health and school participation among untreated children in both treatment schools and neighboring schools, and these externalities are large enough to justify fully subsidizing treatment. Yet we do not find evidence that deworming improved academic test scores. KEYWORDS: Health, education, Africa, externalities, randomized evaluation, worms. 1. INTRODUCTION HOOKWORM, ROUNDWORM, WHIPWORM, and schistosomiasis infect one in four people worldwide. They are particularly prevalent among school-age children in developing countries. We examine the impact of a program in which seventy-five rural Kenyan primary schools were phased into deworming treatment in a randomized order. We find that the program reduced school absenteeism by at least one-quarter, with particularly large participation gains among the youngest children, making deworming a highly effective way to boost school participation among young children. We then identify crossschool externalities the impact of deworming for pupils in schools located near treatment schools using exogenous variation in the local density of treatment school pupils generated by the school-level randomization, and find that deworming reduces worm burdens and increases school participation among 1 The authors thank ICS Africa, the Kenya Ministry of Health Division of Vector Borne Diseases, Donald Bundy, and Paul Glewwe for their cooperation in all stages of the project, and would especially like to acknowledge the contributions of Elizabeth Beasley, Laban Benaya, Pascaline Dupas, Simon Brooker, Alfred Luoba, Sylvie Moulin, Robert Namunyu, Polycarp Waswa, and the PSDP field staff and data group, without whom the project would not have been possible. Gratitude is also extended to the teachers and school children of Busia for participating in the study. George Akerlof, Harold Alderman, Timothy Besley, Peter Hotez, Caroline Hoxby, Lawrence Katz, Doug Miller, Chris Udry, and the editor and four anonymous referees have provided valuable comments. Melissa Gonzalez-Brenes, Andrew Francis, Bryan Graham, Tina Green, Jessica Leino, Emily Oster, Anjali Oza, and Jon Robinson have provided excellent research assistance. The evaluation was sponsored by the World Bank and the Partnership for Child Development, but all viewpoints, as well as any errors, are our own. 159

2 160 E. MIGUEL AND M. KREMER children in neighboring primary schools. There is also some evidence of withinschool treatment externalities, although given that randomization took place across schools, rather than across pupils within schools, we cannot use experimental identification to decompose the overall effect on treatment schools into a direct effect and a within-school externality effect, and must rely on necessarily more tentative nonexperimental methods. Including the externality benefits, the cost per additional year of school participation is only $3.50, making deworming considerably more cost-effective than alternative methods of increasing school participation, such as school subsidies (see Kremer (2003)). Moreover, internalizing these externalities would likely require not only fully subsidizing deworming, but actually paying people to receive treatment. We do not find any evidence that deworming increased academic test scores. However, the school participation gains we estimate are not large enough to generate statistically significant test score gains given the observed crosssectional relationship between school attendance and test scores. There is a large literature documenting positive correlations between health and economic outcomes. Our results suggest a causal link running from health to education. 2 The finding that treatment externalities are large also suggests a potentially important role for subsidies for treatment, especially given that nearly half of Africa s disease burden is due to infectious and parasitic disease (WHO (1999)). Our approach can be distinguished from that in several recent studies in which treatment is typically randomized at the individual level and its educational impact is estimated by comparing cognitive ability among those treatment and comparison pupils who attend a later testing session. Dickson et al. (2000) review these studies and conclude that they do not provide convincing evidence for educational benefits of deworming. However, these studies fail to account for potential externalities for the comparison group from reduced disease transmission. Moreover, if externalities benefit the comparison group, outcome differences between the treatment and comparison groups will understate the benefits of treatment on the treated. This identification problem is closely related to the well-known issue of contamination of experimental job programs in active labor markets, where programs have externality effects on program nonparticipants (typically by worsening their outcomes, as discussed in Heckman, LaLonde, and Smith (1999)). 2 Refer to Strauss and Thomas (1998) for a survey of the literature on health and income. While nonexperimental studies have found that poor early childhood nutrition is associated with delayed primary school enrollment and reduced academic achievement in Ghana (Glewwe and Jacoby (1995)) and the Philippines (Glewwe, Jacoby, and King (2001)), and several prospective studies suggest iron supplementation improves academic outcomes of anemic children (Nokes, van den Bosch, and Bundy (1998)), Behrman s (1996) review argues that given the limited experimental evidence and the difficulty of inferring causality from correlations in nonexperimental data, aside from anemia, the existing literature on child health and education is inconclusive.

3 WORMS: IDENTIFYING IMPACTS 161 We use two approaches to deal with the problem of identification in the presence of local externalities. First, because randomization took place at the level of schools, we are able to estimate the overall effect of deworming on a school even if there are treatment externalities among pupils within the school. Second, we identify cross-school externalities the impact of deworming for pupils in schools located near treatment schools using exogenous variation in the local density of treatment school pupils generated by the school-level randomization. As discussed above, we find large deworming treatment externalities both on health and education, and our analysis suggests that failure to account for these externalities would lead to substantially underestimating the impacts of deworming. The paper is organized as follows. Section 2 reviews the existing literature on helminths and education. Section 3 describes the project we evaluate in rural Kenya and presents the baseline educational and medical characteristics. Section 4 describes the estimation strategy. Sections 5, 6, and 7 discuss the program s effect on health, school participation, and test scores, respectively. Section 8 examines the cost-effectiveness of deworming relative to other ways of improving health and school participation and argues the estimated externalities justify fully subsidizing deworming. The final section summarizes and discusses implications of the results. 2. INTESTINAL HELMINTH (WORM) INFECTIONS Hookworm and roundworm each infect approximately 1.3 billion people around the world, while whipworm affects 900 million and 200 million are infected with schistosomiasis (Bundy (1994)).While most have light infections, which may be asymptomatic, a minority have heavy infections, which can lead to iron-deficiency anemia, protein-energy malnutrition, abdominal pain, and listlessness. 3 Schistosomiasis can also have more severe consequences, for instance, causing enlargement of the liver and spleen. Low-cost single-dose oral therapies can kill the worms, reducing hookworm, roundworm, and schistosomiasis infections by 99 percent, although single-dose treatments are only moderately effective against severe whipworm infections (Butterworth et al. (1991), Nokes et al. (1992), Bennett and Guyatt (2000)). Reinfection is rapid, however, with worm burden often returning to eighty percent or more of its original level within a year (Anderson and May (1991)), and hence geohelminth drugs must be taken every six months and schistosomiasis drugs must be taken annually. The World Health Organization has endorsed mass school-based deworming programs in areas with high helminth infections, since this eliminates the need for costly individual parasitological screening (Warren et al. (1993), WHO (1987)), bringing cost down to as little 3 Refer to Adams et al. (1994), Corbett et al. (1992), Hotez and Pritchard (1995), and Pollitt (1990).

4 162 E. MIGUEL AND M. KREMER as 49 cents per person per year in Africa (PCD (1999)). Known drug side effects are minor, and include stomach ache, diarrhea, dizziness, and vomiting in some cases (WHO (1992)). However, due to concern about the possibility that the drugs could cause birth defects (WHO (1992), Cowden and Hotez (2000)), standard practice in mass deworming programs has been to not treat girls of reproductive age (Bundy and Guyatt (1996)). 4 Medical treatment could potentially interfere with disease transmission, creating positive externalities. School-aged children likely account for the bulk of helminth transmission (Butterworth et al. (1991)). Muchiri, Ouma, and King (1996) find that school children account for 85 to 90 percent of all heavy schistosomiasis infections in nine eastern Kenyan villages. Moreover, conditional on infection levels, children are most likely to spread worm infections because they are less likely to use latrines and more generally have poor hygiene practices (Ouma (1987), Butterworth et al. (1991)). 5 Treatment externalities for schistosomiasis are likely to take place across larger areas than is typical for geohelminth externalities due to the differing modes of disease transmission. Geohelminth eggs are deposited in the local environment when children defecate in the bush surrounding their home or school, while the schistosomiasis parasite is spread through contact with infected fresh water. Children in the area are often infected with schistosomiasis by bathing or fishing in Lake Victoria, and children who live some distance from each other may bathe or fish at the same points on the lake. Moreover, the water-borne schistosome may be carried considerable distances by stream and lake currents, and the snails that serve as its intermediate hosts are themselves mobile. In the absence of frequent reinfection, individual worm burdens are likely to fall rapidly given the relatively short typical life spans of intestinal worms: twelve months for roundworm and whipworm, two years for hookworm, and three years for schistosomiasis (Bundy and Cooper (1989), Anderson and May (1991)), so that if the age of worms within a human host is uniformly distributed, worm burden may halve in six to eighteen months depending on the worm. There is existing only limited empirical evidence on deworming treatment externalities, but that which exists suggests that school-based deworming may create substantial externalities. 6 However, these studies rely on pre-post 4 With a lengthening track record of safe use, this practice is now changing. 5 Animal-human transmission is not a serious concern in this area for hookworm, whipworm, and schistosomiasis (Cambridge University Schistosomiasis Research Group (2000), Corwin (2000)), and is unlikely to be a major concern for roundworm. A roundworm species that predominantly infects pigs (Ascaris suum) may also sometimes infect humans, but is unlikely to be a major problem in this area since fewer than 15 percent of households keep pigs at home. 6 Adult worm burden fell by nearly fifty percent after fifteen months on the island of Montserrat in communities where children were mass treated for worms (Bundy et al. (1990)). We examine four other related studies two of which do not explicitly discuss externalities, but whose published results allow us to compute them and find reductions of up to fifty percent in infec-

5 WORMS: IDENTIFYING IMPACTS 163 comparisons in the same villages to estimate externalities for untreated individuals. This leaves them without a plausible comparison group, which is particularly problematic since infection rates vary widely seasonally and from year to year due to rainfall variation and other factors (Kloos et al. (1997)). The randomized phase-in across schools of the deworming intervention that we examine allows us to capture the overall effect of deworming even in the presence of externalities across individuals within schools. School-level randomization also naturally generates local variation in the density of treatment that we use to estimate spillovers across schools. Our sample of 75 schools is also much larger than existing studies, which were typically conducted in five or fewer villages. The educational impact of deworming is considered a key issue in assessing whether the poorest countries should accord priority to deworming (Dickson et al. (2000)). It has been hypothesized that intense worm infections reduce educational achievement (Bundy (1994), Del Rosso, Miller, and Marek (1996), Drake et al. (1999), Stoltzfus et al. (1997)), either by inducing anemia, which is known to affect educational outcomes (Nokes, van den Bosch, and Bundy (1998)), or through other channels, including protein-energy malnutrition. However, in an influential Cochrane review published in the British Medical Journal, Dickson et al. (2000) claim that the evidence of benefit for mass [deworming] treatment of children related to positive effects on [physical] growth and cognitive performance is not convincing. In light of these data, we would be unwilling to recommend that countries or regions invest in programmes that routinely treat children with anthelmintic drugs. Yet the existing randomized evaluations on worms and education on which Dickson et al. (2000) base their conclusions suffer from several shortcomings. First, existing studies randomize the provision of deworming treatment within schools to treatment and placebo groups, and then examine the impact of deworming on cognitive outcomes. Their within-school randomization designs prevent existing studies from credibly estimating externality benefits. Moreover, the difference in educational outcomes between the treatment and placebo groups understates the actual impact of deworming on the treatment group if placebo group pupils also experience health gains due to local treatment externalities. In fact, re-examination of these recent randomized studies suggests that untreated placebo pupils often experienced substantial worm load reductions, as would be consistent with the hypothesis of within-school externalities. 7 tion intensity among untreated individuals in communities where school children received mass deworming (Butterworth et al. (1991), Holland et al. (1996), Muchiri, Ouma, and King (1996), Thein-Hlaing, Than-Saw, and Myat-Lay-Kyin (1991)). 7 In Simeon, Grantham-McGregor, Callender, and Wong (1995), all pupils started with heavy whipworm infections (over 1200 eggs per gram, epg). Thirty-two weeks into the study, heavy infections fell 95 percent in the treatment group and 43 percent among the placebo group, and treatment and placebo pupils showed an identical gain of 0.3 in body mass index (low body mass index is associated with acute nutritional deficiencies). Simeon, Grantham-McGregor, and Wong

6 164 E. MIGUEL AND M. KREMER A second shortcoming of existing randomized studies is that although they report the impact of deworming on tests of cognitive performance (such as tests of recall), they typically do not examine other outcomes of interest to policymakers, including school attendance, enrollment, academic test scores, or grade promotion. Only two studies examine effects on attendance and both should be interpreted with caution since the data were drawn from attendance registers, which are notoriously inaccurate in many developing countries. Treating growth-stunted Jamaican children with heavy whipworm infections increased school attendance by 9.9 percentage points, reducing absenteeism by one-third (Simeon, Grantham-McGregor, Callender, and Wong (1995)).Thirty-five percent of pupils were missing attendance data. Watkins, Cruz, and Pollitt (1996a, 1996b) find no effect of treatment of roundworm and whipworm on primary school attendance. However, periods of extended school absence are dropped, leading to high rates of recorded attendance (90 percent). If treated pupils were healthier and had fewer inactive periods, this creates attrition bias and will thus understate the true impact of deworming on school attendance. However, nonexperimental studies suggest that worms do affect school participation. 8 To the extent that deworming increases school participation, as we suggest, other existing studies may also suffer serious attrition bias. For example, Nokes et al. (1992) report test score data for 89 percent of students in their treatment group but only 59 percent in their comparison group. (1995), which was conducted among a subsample of the study population in Simeon, Grantham- McGregor, Callender, and Wong (1995), find that median whipworm load fell from 2523 epg for the treatment pupils pre-treatment, to 0 epg after 32 weeks, while among placebo pupils median whipworm load fell from 2946 to 1724 epg, a drop of roughly one-third among placebo pupils. In Nokes et al. (1992), average hookworm infection intensity fell by fifty percent among the placebo pupils (although there was no change in roundworm or whipworm infection for placebo pupils). Since the samples in these studies were selected based on high worm load, the fall in worm load among placebo pupils could potentially be due to mean reversion as well as to externalities. However, Watkins, Cruz, and Pollitt (1996a) did not select their sample based on worm load, and find that mean roundworm epg fell roughly 25 percent among placebo pupils after twenty-four weeks of treatment with albendazole. 8 Geissler et al. (2000) interviewed school children from a nearby region of western Kenya, and argue that worms may caused school absence in five percent of all interviews (and account for nearly half of all absences). Bleakley (2002) finds that areas in the U.S. South with higher hookworm infection levels prior to the Rockefeller Sanitary Commission deworming campaign experienced greater increases in school attendance after the intervention, and estimates that each case of hookworm reduced the number of children attending school by 0.23 (which is similar to our estimates presented below). Although it is difficult to fully rule out omitted variable bias using a nonexperimental approach, an important strength of Bleakley (2002) is that the Rockefeller campaign was introduced throughout a large geographic area, and thus the estimates are not subject to the biases faced by medical studies that randomize treatment at the individual level. (Brinkley (1994) argues that the Rockefeller campaign also dramatically increased agricultural productivity.)

7 WORMS: IDENTIFYING IMPACTS THE PRIMARY SCHOOL DEWORMING PROJECT IN BUSIA, KENYA We evaluate the Primary School Deworming Project (PSDP), which was carried out by a Dutch nonprofit organization, Internationaal Christelijk Steunfonds Africa (ICS), in cooperation with the Busia District Ministry of Health office. The project took place in southern Busia, a poor and densely-settled farming region in western Kenya, in an area with the highest helminth infection rates in Busia district. The 75 project schools consist of nearly all rural primary schools in this area, and had a total enrolment of over 30,000 pupils between ages six to eighteen. In January 1998, the seventy-five PSDP schools were randomly divided into threegroupsoftwenty-fiveschoolseach:theschoolswerefirststratifiedbyadministrative subunit (zone) and by their involvement in other nongovernmental assistance programs, and were then listed alphabetically and every third school was assigned to a given project group. 9 Due to ICS s administrative and financial constraints, the health intervention was phased in over several years. Group 1 schools received free deworming treatment in both 1998 and 1999, Group 2 schools in 1999, while Group 3 schools began receiving treatment in Thus in 1998, Group 1 schools were treatment schools, while Group 2 and Group 3 schools were comparison schools, and in 1999, Group 1 and Group 2 schools were treatment schools and Group 3 schools were comparison schools Baseline Characteristics ICS field staff administered pupil and school questionnaires in early 1998 and again in early Prior to treatment, the groups were similar on most demographic, nutritional, and socioeconomic characteristics, but despite randomized assignment which produces groups with similar characteristics in expectation Group 1 pupils appear to be worse off than Group 2 and 3 pupils along some dimensions, potentially creating a bias against finding significant program effects (Table I). There are no statistically significant differences across Group 1, 2, and 3 schools in enrolment, distance to Lake Victoria, school sanitation facilities, pupils weight-for-age, 10 asset ownership, selfreported malaria, or the local density of other primary school pupils located within three kilometers or three to six kilometers. Helminth infection rates in the surrounding geographic zone are also nearly identical across the three groups. School attendance rates did not differ significantly in early 1998 before the first round of medical treatment, although this baseline attendance 9 Twenty-seven of the seventy-five project schools were also involved in other NGO projects, which consisted of financial assistance for textbook purchase and classroom construction, and teacher performance incentives. Appendix Table AI presents a detailed project timeline. 10 Unfortunately, due to problems with field data collection, we do not have usable baseline height data.

9 WORMS: IDENTIFYING IMPACTS 167 TABLE I (CONTINUED) Group 1 Group 2 Group 3 Group 1 Group 2 (25 schools) (25 schools) (25 schools) Group 3 Group 3 Total primary school pupils within 3 km Total primary school pupils within 3 6 km (205 5) (205 5) (209 5) (209 5) a School averages weighted by pupil population. Standard errors in parentheses. Significantly different than zero at 99 (***), 95 (**), and 90 (*) percent confidence. Data from the 1998 ICS Pupil Namelist, 1998 Pupil Questionnaire and 1998 School Questionnaire. b 1996 District exam scores have been normalized to be in units of individual level standard deviations, and so are comparable in units to the 1998 and 1999 ICS test scores (under the assumption that the decomposition of test score variance within and between schools was the same in 1996, 1998, and 1999). c This includes girls less than 13 years old, and all boys (those eligible for deworming in treatment schools). information comes from school registers, which are not considered reliable in Kenya. To the extent that there were significant differences between treatment and comparison schools, treatment schools were initially somewhat worse off. Group 1 pupils had significantly more self-reported blood in stool (a symptom of schistosomiasis infection), reported being sick more often than Group 3 pupils, and were not as clean as Group 2 and Group 3 pupils (as observed by NGO field workers). They also had substantially lower average scores on 1996 Kenyan primary school examinations than Group 2 and 3 schools, although the difference is not significant at traditional confidence levels. In January and February 1998, prior to treatment, a random sample of ninety grade three to eight pupils (fifteen per grade) in each of the 25 Group 1 schools were selected to participate in a parasitological survey conducted by the Kenya Ministry of Health, Division of Vector Borne Diseases. 11 Ninety-two percent of surveyed pupils had at least one helminth infection and thirty-seven percent had at least one moderate-to-heavy helminth infection (Table II), 12 although these figures understate actual infection prevalence to the extent that the most heavily infected children were more likely to be absent from school on the day of the survey. Worm infection rates are relatively high in this region by international standards, but many other African settings have similar 11 Following the previous literature, infection intensity is proxied for worm eggs per gram (epg) in stool (Medley and Anderson (1985)). Each child in the parasitological sample was given a plastic container and asked to provide a stool sample; samples were examined in duplicate within twenty-four hours using the Kato-Katz method. Group 2 and Group 3 schools were not included in the 1998 parasitological survey since it was not considered ethical to collect detailed health information from pupils who were not scheduled to receive medical treatment in that year. 12 Following Brooker, Miguel, et al. (2000), thresholds for moderate infection are 250 epg for Schistosomiasis. mansoni and 5,000 epg for Roundworm, the WHO standards, and 750 epg for Hookworm and 400 epg for Whipworm, both somewhat lower than the WHO standard.

10 168 E. MIGUEL AND M. KREMER TABLE II JANUARY 1998 HELMINTH INFECTIONS, PRE-TREATMENT, GROUP 1SCHOOLS a Prevalence of Prevalence of Average infection infection moderate-heavy intensity, in infection eggs per gram (s.e.) Hookworm (1055) Roundworm (5156) Schistosomiasis, all schools (413) Schistosomiasis, schools <5 km from Lake Victoria (879) Whipworm (470) At least one infection Born since Born before Female Male At least two infections At least three infections a These are averages of individual-level data, as presented in Brooker, Miguel, et al. (2000); correcting for the oversampling of the (numerically smaller) upper grades does not substantially change the results. Standard errors in parentheses. Sample size: 1894 pupils. Fifteen pupils per standard in grades 3 to 8 for Group 1 schools were randomly sampled. The bottom two rows of the column Prevalence of moderate-heavy infection should be interpreted as the proportion with at least two or at least three moderate-to-heavy helminth infections, respectively. The data were collected in January to March 1998 by the Kenya Ministry of Health, Division of Vector Borne Diseases (DVBD). The moderate infection thresholds for the various intestinal helminths are: 250 epg for S. mansoni, and 5,000 epg for Roundworm, both the WHO standard, and 750 epg for Hookworm and 400 epg for Whipworm, both somewhat lower than the WHO standard. Refer to Brooker, Miguel, et al. (2000) for a discussion of this parasitological survey and the infection cut-offs. All cases of schistosomiasis are S. mansoni. infection profiles (Brooker, Rowlands, et al. (2000)). Moderate-to-heavy worm infections are more likely among younger pupils and among boys. Pupils who attend schools near Lake Victoria also have substantially higher rates of schistosomiasis. Latrine ownership is negatively correlated with moderate-to-heavy infection (results not shown) The Intervention Following World Health Organization recommendations (WHO (1992)), schools with geohelminth prevalence over 50 percent were mass treated with albendazole every six months, and schools with schistosomiasis prevalence over 30 percent were mass treated with praziquantel annually. 13 All treatment 13 The medical protocol was designed in collaboration with the Partnership for Child Development, and was approved by the Ethics Committee of the Kenya Ministry of Health and Busia

11 WORMS: IDENTIFYING IMPACTS 169 schools met the geohelminth cut-off in both 1998 and Six of twenty-five treatment schools met the schistosomiasis cut-off in 1998 and sixteen of fifty treatment schools met the cut-off in Medical treatment was delivered to the schools by Kenya Ministry of Health public health nurses and ICS public health officers. Following standard practice (Bundy and Guyatt (1996)), the medical protocol did not call for treating girls thirteen years of age and older due to concerns about the potential teratogenicity of the drugs (WHO (1992)). 15 In addition, treatment schools received worm prevention education through regular public health lectures, wall charts, and the training of teachers in each treatment school on worm prevention. Health education stressed the importance of hand washing to avoid ingesting roundworm and whipworm larvae, wearing shoes to avoid hookworm infection, and not swimming in infected fresh water to avoid schistosomiasis. ICS obtained community consent in all treatment schools in A series of community and parent meetings were held in treatment schools, at which the project was described and parents who did not want their child to participate in the project were asked to inform the school headmaster. Under the recommendation of the Kenya Ministry of Health, beginning in January 1999 ICS required signed parental consent for all children to receive medical treatment; consent typically took the form of parents signing their name in a notebook kept at school by the headmaster. This is not a trivial requirement for many households: travelling to school to sign the book may be time-consuming, and some parents may be reluctant to meet the headmaster when behind on school fees, a common problem in these schools. District Medical Officer of Health. The 30 percent threshold for mass praziquantel treatment is less than the WHO standard of 50 percent, although in practice few schools had schistosomiasis prevalence between 30 to 50 percent. Pupils in the parasitological subsample who were found to be infected with schistosomiasis, but attended schools that did not qualify for mass treatment with praziquantel, were individually treated. However, there were few such pupils: the proportion of moderate-to-heavy schistosomiasis among the thirty-four schools that fell below the 30 percent threshold in 1999 was just In 1998, pupils received 600 mg albendazole doses during each round of treatment, following the protocol of an earlier Government of Kenya Ministry of Health deworming project in Kwale District; in 1999, pupils were treated with 400 mg albendazole (WHO (1992)). Praziquantel was provided at approximately 40 mg/kg (WHO (1992)) in both 1998 and The NGO used generic drugs in 1998, and SmithKline Beecham s Zentel (albendazole) and Bayer s Biltricide (praziquantel) in Pregnancy test reagent strips are not practical during mass treatment (Bundy and Guyatt (1996)). Personal interviews (i.e., asking girls when they had their most recent menstrual period) may not be effective in determining pregnancy in this setting because pregnant girls might fear that the information would not be held in confidence; pregnant girls are often expelled from Kenyan primary schools (although this is not official government policy).

12 170 E. MIGUEL AND M. KREMER 3.3. Assigned and Actual Deworming Treatment Seventy-eight percent of those pupils assigned to receive treatment (i.e., girls under thirteen years old and all boys in the treatment schools) received at least some medical treatment through the program in 1998 (Table III). 16 Since approximately 80 percent of the students enrolled prior to the start of the pro- TABLE III PROPORTION OF PUPILS RECEIVING DEWORMING TREATMENT IN PSDP a Group 1 Group 2 Group 3 Girls <13 Girls Girls <13 Girls Girls <13 Girls years, and 13 years years, and 13 years years, and 13 years all boys all boys all boys Treatment Comparison Comparison Any medical treatment in (For grades 1 8 in early 1998) Round 1 (March April 1998), Albendazole Round 1 (March April 1998), Praziquantel b Round 2 (Oct. Nov. 1998), Albendazole Treatment Treatment Comparison Any medical treatment in (For grades 1 7 in early 1998) Round 1 (March June 1999), Albendazole Round 1 (March June 1999), Praziquantel b Round 2 (Oct. Nov. 1999), Albendazole Any medical treatment in (For grades 1 7 in early 1998), among pupils enrolled in 1999 Round 1 (March June 1999), Albendazole Round 1 (March June 1999), Praziquantel b Round 2 (Oct. Nov. 1999), Albendazole a Data for grades 1 8. Since month of birth information is missing for most pupils, precise assignment of treatment eligibility status for girls born during the threshold year is often impossible; all girls who turn 13 during a given year are counted as 12 year olds (eligible for deworming treatment) throughout for consistency. b Praziquantel figures in Table III refer only to children in schools meeting the schistosomiasis treament threshold (30 percent prevalence) in that year. 16 In what follows, treatment schools refer to all twenty-five Group 1 schools in 1998, and all fifty Group 1 and Group 2 schools in 1999.

13 WORMS: IDENTIFYING IMPACTS 171 gram were present in school on a typical day in 1998, absence from school on the day of drug administration was a major cause of drug noncompliance. Nineteen percent of girls thirteen years of age or older also received medical treatment in This was partly because of confusion in the field about pupil age, and partly because in the early stages of the program several of the Kenya Ministry of Health nurses administered drugs to some older girls, judging the benefits of treatment to outweigh the risks. This was particularly common in schools near the lake where schistosomiasis was more of a problem. A somewhat lower proportion of pupils in school took the medicine in Among girls younger than thirteen and boys who were enrolled in school for at least part of the 1999 school year, the overall treatment rate was approximately 72 percent (73 percent in Group 1 and 71 percent in Group 2 schools), suggesting that the process of selection into treatment was fairly similar in the two years despite the change in consent rules. Of course, measured relative to the baseline population of students enrolled in early 1998, a smaller percentage of students were still in school in 1999 and hence, treatment rates in this baseline sample were considerably lower in 1999 than in 1998: among girls under thirteen years of age and all boys in treatment schools from the baseline sample, approximately 57 percent received medical treatment at some point in 1999, while only nine percent of the girls thirteen years of age and older received treatment. 17 Only five percent of comparison school pupils received medical treatment for worms independently of the program during the previous year, according to the 1999 pupil questionnaire. 18 An anthropological study examining worm treatment practices in a neighboring district in Kenya (Geissler et al. (2000)), finds that children self-treat the symptoms of helminth infections with local herbs, but found no case in which a child or parent purchased deworming 17 The difference between the 72 percent and 57 percent figures is due to Group 2 pupils who dropped out of school (or who could not be matched in the data cross years, despite the efforts of the NGO field staff) between years 1 and 2 of the project. Below, we compare infection outcomes for pupils who participated in the 1999 parasitological survey, all of whom were enrolled in school in Thus the parasitological survey sample consists of pupils enrolled in school in both 1998 and 1999 for both the treatment and comparison schools. To the extent that the deworming program itself affected enrolment outcomes 1999 school enrolment is approximately four percentage points higher in the treatment schools than the comparison schools the pupils enrolled in the treatment versus comparison schools in 1999 will have different characteristics. However, since drop-out rates were lower in the treatment schools, this is likely to lead to a bias toward zero in the within-school health externality estimates, in which case our estimates serve as lower bounds on true within-school effects. 18 A survey to assess the availability of deworming drugs in this area, conducted during May to July 1999, found no local shops surveyed carried either WHO-recommended broad-spectrum treatments for geohelminths (albendazole and mebendazole) or schistosomiasis (praziquantel) in stock on the day of the survey, though a minority carried cheaper but less effective drugs (levamisole hydrochloride and piperazine). Some clinics and pharmacies carried broad-spectrum drugs, but these were priced far out of range for most of the population.

14 172 E. MIGUEL AND M. KREMER TABLE IV PROPORTION OF PUPIL TRANSFERS ACROSS SCHOOLS 1998 transfer to a 1999 transfer to a School in early 1998 Group 1 Group 2 Group 3 Group 1 Group 2 Group 3 (pre-treatment) school school school school school school Group Group Group Total transfers drugs. To the extent that children in Busia also self-treat helminth symptoms with herbs, in this study we measure the net benefit of deworming drugs above and beyond the impact of herbs and of any individually purchased medicines. Although pupils assigned to comparison schools could also potentially have transferred to treatment schools to receive deworming medical treatment through the program, there is no evidence of large asymmetric flows of pupils into treatment schools, which could bias the results (Table IV). Among sample pupils, approximately two percent transferred into a different school in 1998, with nearly equal proportions transferring into Groups 1, 2, and 3 schools, and approximately eight percent of pupils had transferred into a different school by the end of 1999, again with similar proportions transferring to all three groups (the transfer rates from early 1998 through the end of 1999 are substantially higher than rates through the end of 1998 because most transfers occur between school years). As we discuss in Section 4, we also use a standard intention-to-treat (ITT) estimation strategy, in which pupils are assigned the treatment status of the school in which they were initially enrolled in early 1998 even if they later switched schools, to address potential transfer bias Health Outcome Differences Between Group 1 and Group 2 Schools Before proceeding to formal estimation in Section 4, we present simple differences in health outcomes between treatment and comparison schools, although as we discuss below, these differences understate overall treatment effects if there are deworming treatment externalities across schools. The Kenyan Ministry of Health conducted a parasitological survey of grade three to eight pupils in Group 1 and Group 2 schools in January and February 1999, one year after the first round of treatment but before Group 2 schools had been treated. Overall, 27 percent of pupils in Group 1 (1998 treatment) schools had a moderate-to-heavy helminth infection in early 1999 compared to 52 percent in Group 2 (1998 comparison) schools, and this difference is significantly different than zero at 99 percent confidence (Table V). The prevalences of moderate-to-heavy hookworm, roundworm, schistosomiasis, and whipworm infections were all lower in Group 1 (1998 treatment) schools than in Group 2

16 174 E. MIGUEL AND M. KREMER (1998 comparison) schools. The program was somewhat less effective against whipworm, perhaps as a result of the lower efficacy of single-dose albendazole treatments for whipworm infections, as discussed above. 19 Note that it is likely that substantial reinfection had occurred during the three to twelve months between 1998 deworming treatment and the 1999 parasitological surveys, so differences in worm burden between treatment and comparison schools were likely to have been even greater shortly after treatment. In addition, to the extent that pupils prone to worm infections are more likely to be present in school on the day of the parasitological survey in the Group 1 schools than the Group 2 schools due to deworming health gains, these average differences between Group 1 and Group 2 schools are likely to further understate true deworming treatment effects. Group 1 pupils also reported better health outcomes after the first year of deworming treatment: four percent fewer Group 1 pupils reported being sick in the past week, and three percent fewer pupils reported being sick often (these differences are significantly different than zero at 95 percent confidence). Group 1 pupils also had significantly better height-for-age a measure of nutritional status by early 1999, though weight-for-age was no greater on average. 20 Although Group 1 pupils had higher hemoglobin concentrations than Group 2 pupils in early 1999, the difference is not statistically different than zero. Recall that anemia is the most frequently hypothesized link between worm infections and cognitive performance (Stoltzfus et al. (1997)). Severe anemia is relatively rare in Busia: fewer then 4 percent of pupils in Group 2 schools (comparison schools in 1998) fell below the Kenya Ministry of Health anemia threshold of 100 g/l in early 1999 before deworming treatment. This is low relative to many other areas in Africa, of which many have substantial helminth problems: a recent survey of studies of anemia among school children in less developed countries (Hall and Partnership for Child Development (2000)) indicates that there is considerably less anemia in Busia than in samples from Ghana, Malawi, Mali, Mozambique, and Tanzania The rise in overall moderate-to-heavy helminth infections between 1998 and 1999 (refer to Table II) is likely to be due to the extraordinary flooding in 1998 associated with the El Niño weather system, which increased exposure to infected fresh water (note the especially large increases in moderate-to-heavy schistosomiasis infections), created moist conditions favorable for geohelminth larvae, and led to the overflow of latrines, incidentally also creating a major outbreak of fecal-borne cholera. 20 Although it is somewhat surprising to find height-for-age gains but not weight-for-age gains, since the latter are typically associated with short-run nutritional improvements, it is worth noting that Thein-Hlaing, Thane-Toe, Than-Saw, Myat-Lay-Kyin, and Myint-Lwin s (1991) study in Myanmar finds large height gains among treated children within six months of treatment for roundworm while weight gains were only observed after twenty-four months, and Cooper et al. (1990) present a similar finding for whipworm, so the result is not unprecedented. 21 One possible explanation for low levels of anemia in this area is geophagy (soil eating): Geissler et al. (1998) report that 73 percent of a random sample of children aged in a

17 WORMS: IDENTIFYING IMPACTS 175 Health education had a minimal impact on behavior, so to the extent the program improved health, it almost certainly did so through the effect of anthelmintics rather than through health education. There are no significant differences across treatment and comparison school pupils in early 1999 in three worm prevention behaviors: observed pupil cleanliness, 22 the proportion of pupils wearing shoes, or self-reported exposure to fresh water (Table V). 4. ESTIMATION STRATEGY 4.1. Econometric Specifications Randomization of deworming treatment across schools allows estimation of the overall effect of the program by comparing treatment and comparison schools, even in the presence of within-school externalities. 23 However, externalities may take place not only within, but also across schools, especially since most people in this area live on their farms rather than being concentrated in villages, and neighbors (and even siblings) often attend different schools since there is typically more than one primary school within walking distance. Miguel and Gugerty (2002) find that nearly one-quarter of all households in this area have a child enrolled in a primary school which is not the nearest one to their home. We estimate cross-school externalities by taking advantage of variation in the local density of treatment schools induced by randomization. Although randomization across schools makes it possible to experimentally identify both the overall program effect and cross-school externalities, we must rely on nonexperimental methods to decompose the effect on treated schools into a direct effect and within-school externality effect. We first estimate program impacts in treatment schools, as well as crossschool treatment externalities: 24 (1) Y ijt = a + β 1 T 1it + β 2 T 2it + X ijt δ + d + u i + e ijt (γ d N T dit ) + d (φ d N dit ) neighboring region of Western Kenya reported eating soil daily. Given the average amount of soil children were observed eating daily, and the measured mean iron content of soil in this area, Geissler et al. conclude that soil provides an average of 4.7 mg iron per day over one-third of the recommended daily iron intake for children. Unfortunately, geophagy could also increase exposure to geohelminth larvae, promoting reinfection. 22 This also holds controlling for initial 1998 levels of cleanliness, or using a difference-indifferences specification. 23 Manski (2000) suggests using experimental methods to identify peer effects. Other recent papers that use group-level randomization of treatment to estimate peer effects include Duflo and Saez (2002) and Miguel and Kremer (2002). Katz, Kling, and Liebman (2001), Kremer and Levy (2001), and Sacerdote (2001) use random variation in peer group composition to estimate peer effects. 24 For simplicity, we present the linear form, but we use probit estimation below for discrete dependent variables.

18 176 E. MIGUEL AND M. KREMER Y ijt is the individual health or education outcome, where i refers to the school, j to the student, and t {1 2} to the year of the program; T 1it and T 2it are indicator variables for school assignment to the first and second year of deworming treatment, respectively; and X ijt are school and pupil characteristics. N dit is the total number of pupils in primary schools at distance d from school i in year t, and N T dit is the number of these pupils in schools randomly assigned to deworming treatment. For example, in Sections 5 and 6, d = 03 denotes schools that are located within three kilometers of school i,andd = 36 denotes schools that are located between three to six kilometers away. 25 Individual disturbance terms are assumed to be independent across schools, but are allowed to be correlated for observations within the same school, where the school effect is captured in the u i term. Since local population density may affect disease transmission, and since children who live or attend school near treatment schools could have lower environmental exposure to helminths, which would lead to less reinfection and lower worm burdens, worm burden may depend on both the total number of primary school pupils (N dit ) and the number of those pupils in schools randomly assigned to deworming treatment (N T dit ) within a certain distance from school i in year t of the program. 26 Given the total number of children attending primary school within a certain distance from the school, the number of these attending schools assigned to treatment is exogenous and random. Since any independent effect of local school density is captured in the N dit terms, the γ d coefficients measure the deworming treatment externalities across schools. In this framework β 1 + (γ d dn T dit ) is the average effect of the first year of deworming treatment on overall infection prevalence in treatment schools, where N T dit is the average number of treatment school pupils located at distance d from the school, and β 2 + (γ d dn T dit ) is the analogous effect for the second year of deworming. β 1 and β 2 capture both direct effects of deworming treatment on the treated, as well as any externalities on untreated pupils within the treatment schools Under spatial externality models in which a reduction in worm prevalence at one school affects neighboring schools and this in turn affects their neighbors, some externalities would spill over beyond six kilometers. To the extent that there are externalities beyond six kilometers from the treatment schools, equation (1) yields a lower bound on treatment effects, but we think any such spillovers are likely to be relatively minor in this setting. 26 Since cross-school externalities depend on the number of pupils eligible for treatment rather than the total number of pupils, we use the number of girls less than 13 years old and all boys (the pupils eligible for deworming in the treatment schools) as the school population (N dit and N T dit ) for all schools in the remainder of the paper. Measurement error in GPS locations due to U.S. government downgrading of GPS accuracy until May 2000 leads to attenuation bias, making it more difficult to find treatment externalities. 27 Unfortunately, we do not have data on the location of pupils homes, and hence cannot examine if pupils living near treatment schools actually obtain greater externality benefits.

19 WORMS: IDENTIFYING IMPACTS 177 The assigned deworming treatment group is not significantly associated with the density of other local treatment school pupils within three kilometers or within three to six kilometers (Table I); in other words, approximately as many treated pupils are located near Group 1 schools as near Group 2 or 3 schools. The 1998 and 1999 deworming compliance rates are also not significantly associated with the local density of treatment school pupils conditional on the total local density (Appendix Table AII). Cross-school deworming externalities are likely to increase with the proportion of the local population that receives deworming treatment. Although the school-level randomization induced a range of variation in local treatment densities in our sample, with only 49 schools we cannot estimate how marginal externalities vary with local treatment levels. 28 Yet since large-scale deworming programs in most poor countries would likely use community consent for treatment, rather than individual parental consent as in the first year of the program we examine we estimate the likely extent of treatment externalities under conditions of interest to public health policymakers. Including school and pupil variables X ijt controls for those pre-treatment differences across schools that were present despite randomization, increasing statistical precision. These controls include the average school score on the 1996 Kenya government district exams for grades 5 to 8; 29 the prevalence of moderate-to-heavy helminth infections in the pupil s grade and geographic zone (the pre-treatment average); indicators for school involvement in other nongovernmental organization assistance projects; time controls (indicator variables for each six-month period capture the downward trend in school participation due to dropouts); and grade cohort indicator variables Estimating Within-School Externalities Because randomization was conducted at the level of schools, rather than individuals within schools, it is possible to both estimate the overall treatment effect on treated schools and to conduct a cost-benefit analysis using equation (1). However, it is not possible to experimentally decompose the effect for treatment schools into a direct effect on treated pupils and an externality effect on untreated pupils within treatment schools. It is not valid to use assignment to a treatment school as an instrumental variable for actual medical treatment 28 Quadratic terms of local treatment densities are not significantly related to the rate of any moderate-to-heavy helminth infection (results not shown), and thus we opt to focus on the linear specification, as in equation (1). 29 Average school scores from 1996 two years before the first year of the project were employed since the district exam was not offered in 1997 due to a national teacher strike. Average school exam scores are used because individual exam results are incomplete for However, the 1996 scores are corrected to be in units of individual level standard deviations, and are thus comparable to the 1998 and 1999 test scores under the assumption that the decomposition of test score variance within and between schools was the same in 1996, 1998, and 1999.

20 178 E. MIGUEL AND M. KREMER in the presence of such externalities (Angrist, Imbens, and Rubin (1996)) since the exclusion restriction fails to hold: assignment to a treatment school affects pupil health through externalities, rather than only through the likelihood of receiving medical treatment. In thinking about nonexperimental approaches to such a decomposition, it is worth bearing in mind that there is no evidence that sicker pupils were more likely to obtain deworming treatment; in fact if anything, the evidence seems more consistent with the hypothesis that pupils with higher worm load were somewhat less likely to obtain treatment, either because they were less likely to be in school on the day of treatment or because their households were less willing and able to invest in health. As Panels A and B in Table VI indicate, among girls under 13 and all boys, the children who would remain untreated were slightly more likely to be moderately to heavily infected prior to the intervention than those who ultimately obtained treatment, both for Group 1 schools (in 1998) and Group 2 schools (in 1999). Among girls at least 13 years of age, there is little difference in 1998 infection rates (prior to treatment) between Group 1 pupils who later obtained treatment and those who did not, while the Group 2 pupils who later obtained treatment were substantially less likely to have been moderately to heavily infected in early 1999 than their counterparts who later went untreated. As suggested above, a major cause of missing treatment is school absenteeism: a 2001 parent survey indicates that most noncompliance from absenteeism is due to pupil illness, and we show in Section 6 that pupils with worms miss school more often. Poorer pupils may also have lower compliance if parents who have not paid school fees are reluctant to visit the headmaster to provide consent. We assume in what follows that children obtain treatment if the net gain from treatment is more than a cut-off cost. Formally, D 1ij = 1(S(X ijt e ijt ) + ε ijt >C t ),whered 1ij takes on a value of one if individual j in school i received treatment in the first year that her school was eligible for treatment (1998 for Group 1, 1999 for Group 2), and zero otherwise; here, 1( ) is the indicator function, C t is the total cost to the household of obtaining treatment in year t (which varies between the two years due to the changing consent requirements), and ε ijt is an unobserved random variable that could depend on the distance of the pupil s home from school, or whether the pupil was sick on the treatment day, for example. Given that there was no randomization of treatment within schools, Group 1 pupils who did not receive treatment in 1998 are compared to Group 2 pupils who did not receive treatment in 1999, the year that Group 2 schools were incorporated into treatment, to at least partially deal with potential bias due to selection into medical treatment. For the health outcomes, we compare these two groups as of January to February 1999, when Group 1 schools had already been treated (in 1998) but Group 2 schools had not, while for school participation we compare Groups 1 and 2 during the first year of treatment.

22 180 E. MIGUEL AND M. KREMER As we discussed above, the parental consent rules changed between 1998 and 1999, leading to a reduction in the fraction of pupils receiving treatment within treatment schools. Thus, restricting the sample to Group 1 and Group 2 schools (and holding the X ijt terms constant for the moment, for clarity): (2) E(Y ij1 T 1i1 = 1 X ij1 D 1ij = 0) E(Y ij1 T 1i1 = 0 X ij1 D 1ij = 0) = β 1 + γ d [E(N T T di1 1i1 = 1 D 1ij = 0) d E(N T T di1 1i1 = 0 D 1ij = 0) ] + γ d [E(N di1 T 1i1 = 1 D 1ij = 0) E(N di1 T 1i1 = 0 D 1ij = 0)] d +[E(e ij1 T 1i1 = 1 X ij1 D 1ij = 0) E(e ij1 T 1i1 = 0 X ij1 D 1ij = 0)] where T 1i1 is the treatment assignment of the school in 1998 (t = 1), andthis takes on a value of one for Group 1 and zero for Group 2 schools. The first term on the right-hand side of the equation (β 1 ) is the within-school externality effect. The second and third terms are effects due to differing local densities of primary schools between treatment and comparison schools; these are approximately zero (as we show in Table I) and in any case we are able to control for these densities in the estimation. The key final term, which can be rewritten as E(e ij1 T 1i1 = 1 X ij1 C 1 S(X ij1 e ij1 )>ε ij1 ) E(e ij1 T 1i1 = 0 X ij1 C 2 S(X ij2 e ij2 )>ε ij2 ) captures any unobserved differences between untreated pupils in the Group 1 and Group 2 schools. If C 1 = C 2, then by randomization this term equals zero and (2) can be used to estimate β 1. However, it is likely that C 2 >C 1 due to imposition of the signed parental consent requirement in In our sample, infected people are no more likely to be treated and in fact seem somewhat less likely to be treated and this is robust to conditioning on the full set of X ijt variables described above (results not shown). 30 If S is in fact nondecreasing in e ijt (which can be thought of as unobserved characteristics associated with good health outcomes in this specification), then C 2 >C 1 implies that the final term will be zero or negative, so the left-hand side of the equation will if anything underestimate the within-school externality, β In other words, due to changes in the process of selection into treatment, some Group 2 pupils who would have been treated had they been in Group 1 were in fact not treated in 1999, and this implies that average unobservables e ijt will be at least as great among the untreated in Group 2 as among the untreated in Group 1 (and also 30 Pooling 1998 data for Group 1 pupils and 1999 data for Group 2 pupils, the estimated marginal effect of a moderate-to-heavy infection on drug take-up is 0 008, and this effect is not significantly different than zero. 31 This claim also relies on the assumption that individual e ijt terms are autocorrelated across the two years.

23 WORMS: IDENTIFYING IMPACTS 181 that average e ijt will also be at least as great among the treated Group 2 as among the treated Group 1). The change in overall infection rates between the first two years of the program (captured in X ijt in the above model) may also have affected individual deworming treatment decisions. Infection rates changed across years both due to sizeable cross-school treatment externalities associated with the program, which acted to reduce infection levels, as well as to natural intertemporal variation (e.g., the 1998 flooding) which led to higher rates of moderate-to-heavy infection. This second effect appears to have dominated, leading to higher overall infection rates in 1999 relative to 1998 (Tables II and V), and complicating efforts to sign the direction of the bias in the within-school externality estimates. However, the fact that fewer people obtained treatment in year 2 than year 1 suggests that overall, given the changed consent requirements, the process of selection into treatment became more stringent, so that it is plausible that e ijt is at least as great among the Group 2 pupils who were untreated in their first year of eligibility as among Group 1 pupils who were untreated in their first year of eligibility. Turning to the data suggests that Group 1 pupils untreated in 1998 and Group 2 pupils untreated in 1999 are in fact similar, and that any bias is likely to be small. First, as noted earlier, moderate-to-heavily infected pupils are no more likely to seek treatment than their less infected fellow pupils. Second, there are no statistically significant differences between the Group 1 pupils untreated in 1998 and the Group 2 pupils untreated in 1999 in five baseline characteristics likely to be associated with child health latrine ownership, grade progression, weight-for-age, self-reported health status, and cleanliness and point estimates suggest that the Group 1 untreated pupils are actually somewhat less healthy, less clean, and less likely to have access to a latrine than their counterparts in Group 2 (Table VI, Panel A). 32 These results are consistent with the hypothesis that e ijt in part reflects differences among households in ability and willingness to take action to improve their children s health, and that those pupils with high values of e ijt were somewhat more likely to obtain treatment. 33,34 A further piece of evidence comes from comparing the initial moderateheavy infection rates (in early 1998) of Group 1 pupils treated in 1998 and 32 The analogous comparison with the larger sample used in the school participation estimation (in Table IX) also suggests that Group 1 pupils untreated in 1998 and the Group 2 pupils untreated in 1999 are similar along these characteristics (results not shown). 33 In other words, as the cost of treatment increased between years 1 and 2, the individuals who still opted to receive treatment in year 2 those with higherε ijt, conditional on observables had higher values of e ijt than the individuals who were not treated in year 2 but would have been treated given the year 1 cost. Thus e ijt and ε ijt must be positively correlated among these individuals at the margin of receiving treatment. 34 We have also calculated Manski bounds on within-school externalities in the presence of selection into treatment, but these are largely uninformative given the change in take-up between 1998 and 1999 (results not shown).

24 182 E. MIGUEL AND M. KREMER treated in 1999, to those treated in 1998 but not treated in 1999; this is not a perfect comparison, since Group 1 pupils were in their second year of treatment in 1999, while Group 2 pupils were experiencing their first year of treatment in 1999, but it still provides useful information on how changing the costs of treatment affects take-up. We find that the initial 1998 infection rates of the Group 1 pupils treated in 1999 and those untreated in 1999 differ by less than one percentage point (results not shown), providing further evidence that the change in consent rules between 1998 and 1999 did not substantially change the health status of those who chose to receive treatment through the program. If the expectation of e ij1 is the same for the Group 1 pupils who missed their first year of treatment in 1998, and the Group 2 pupils who missed treatment in 1999, then we can estimate both within-school and cross-school treatment externalities in 1998 using equation (3): (3) Y ijt = a + β 1 T 1it + b 1 D 1ij + b 2 (T 1it D 1ij ) + X δ ijt + (γ d N T ) + dit (φ d N dit ) + u i + e ijt d d Here, β 1 is the within-school externality effect on the untreated, and (β 1 + b 2 ) is the sum of the within-school externality effect plus the additional direct effect of treatment on the treated. If the final term in equation (2) is negative, as we suggest above, this specification underestimates within-school externalities and overstates the impact on the treated within treatment schools; of course, the estimation of overall program effects based on equation (1) is independent of the decomposition into effects on the treated and untreated within treatment schools. The total externality effect for the untreated in treatment schools is the sum of the within-school externality term and the cross-school externality in equation (3). In certain specifications we interact the local pupil density terms with the treatment school indicator to estimate potentially differential cross-school externalities in treatment and comparison schools Initial Evidence on Within-School Deworming Externalities Before presenting results using this unified estimation framework in Sections 5, 6, and 7, we preview the within-school externality results by comparing the January March 1999 infection levels of the Group 1 pupils who did not receive treatment in 1998 and the Group 2 pupils who did not receive treatment in 1999 (the year that Group 2 schools were incorporated into the treatment group). Among girls under thirteen years of age and all boys those children who were supposed to receive medical treatment through the project rates of moderate-to-heavy infections were 21 percentage points lower among Group 1 pupils who did not receive medical treatment in 1998 (34 percent) than among Group 2 pupils who did not receive treatment in 1999 (55 percent), and this difference is significant at 95 percent confidence (Table VI). These differences are negative and statistically significant for hookworm and roundworm, and

25 WORMS: IDENTIFYING IMPACTS 183 negative but insignificant for schistosomiasis and whipworm; since the overall difference in whipworm infection between Group 1 and 2 schools was minimal, and there is evidence that single-dose albendazole treatments are sometimes ineffective against whipworm, it is not surprising that evidence of within-school externalities is weaker for whipworm. By way of contrast, Group 1 pupils who were treated in 1998 had a 24 percent chance of moderate-to-heavy infection in January to February 1999, while Group 2 pupils who would obtain treatment later in 1999 had a 51 percent chance of infection, for a difference of 27 percentage points. Thus at the time infection status was measured in early 1999, the difference in the prevalence of moderate-to-heavy infections among the untreated was approximately three-quarters the difference in prevalence for the treated (21 versus 27 percentage points). The relatively large ratio of externality benefits to benefits for the treated is plausible given the timing of 1998 treatment and the 1999 parasitological survey. Following treatment of part of a population at steady-state worm infection intensity, the treated group will be reinfected over time and their worm load will asymptote to its original level. As discussed in Section 2, other studies have found that prevalence of hookworm, roundworm, and schistosomiasis falls by over 99 percent immediately after treatment, but that reinfection occurs rapidly. On the other hand, worm load among the untreated will gradually fall after the treatment group is dewormed, since the rate of infection transmission declines. Eventually, however, worm load among the untreated will rise again, asymptoting to its original steady-state level as the treated population becomes reinfected. The ratio of worm load among the treated to that among the untreated then approaches one over time. Since we collect data on worm infections some time after treatment the January March 1999 parasitological survey was carried out nearly one year after the first round of medical treatment and three to five months since the second round of treatment and worm loads among the treated are substantial by this point, it seems reasonable to think that reinfection subsequent to the date of treatment accounts for much of observed worm load, and that the average difference in prevalence between treatment and comparison schools over the course of the year was likely to have been considerably greater than the difference observed in early Two additional sources of evidence are consistent with positive within-school deworming treatment externalities. First, although girls aged 13 years and older were largely excluded from deworming treatment, moderate-to-heavy infection rates among older girls in Group 1 schools were ten percentage points lower than among similar girls in Group 2 schools, though this difference is not significantly different than zero (Table VI, Panel B) It is not surprising that the magnitude of within-school externalities is somewhat smaller for older girls than for the population as a whole since these girls have lower rates of moderate to heavy infection (Table II), and are also twice as likely to wear shoes (results not shown), limiting reinfection. As a robustness check, we also estimate equation (3) using an instrumental variables

26 184 E. MIGUEL AND M. KREMER Second, a parasitological survey of 557 children entering preschool who had not yet had any opportunity to receive medical treatment through the program found that in early 2001, before Group 3 schools had begun receiving deworming treatment, children entering preschool in Group 1 and 2 schools had 7.1 percentage points fewer moderate-to-heavy hookworm infections than those entering Group 3 schools, an effect that is significantly different than zero at 90 percent confidence (results not shown). Given that only 18.8 percent of the Group 3 preschool children suffered from moderate-to-heavy hookworm infections, this constitutes a forty percent reduction in the proportion of such infections. The effects for the other worms were not statistically significant, which is not surprising for whipworm, since the direct treatment effects were small, or for schistosomiasis for which externalities likely are less localized, and may not be as relevant for young children who are likely to stay near home, rather than going fishing in Lake Victoria but is somewhat unexpected for roundworm (note, however, that Nokes et al. (1992) also find externalities for hookworm but not other geohelminths). 5. DEWORMING TREATMENT EFFECTS ON HEALTH AND NUTRITION Formal estimation confirms that children in deworming treatment schools experienced a range of health benefits, and provides evidence that these benefits spilled over both to nontreated pupils in the treatment schools and to pupils in neighboring schools. Consistent with the differing modes of disease transmission, geohelminth externalities were primarily within schools, while schistosomiasis externalities were primarily across schools. Estimation of equation (1) indicates that the proportion of pupils with moderate to heavy infection is 25 percentage points lower in Group 1 schools than Group 2 schools in early 1999 and this effect is statistically significant at 99 percent confidence (Table VII, regression 1). We next estimate equation (3), which decomposes the effect of the program on treated schools into an effect on treated pupils and a within-school externality effect. The within-school externality effect, given by the coefficient estimate on the Group 1 indicator variable, is a 12 percentage point reduction in the proportion of moderate-toheavy infections, while the additional direct effect of deworming treatment is approximately 14 percentage points, and both of these coefficient estimates are significantly different than zero (Table VII, regression 2). Children who attend primary schools located near Group 1 schools had lower rates of moderateto-heavy helminth infection in early 1999: controlling for the total number of approach, instrumenting for actual deworming treatment with an indicator variable taking on a value of one for girls under 13 years of age and for all boys interacted with the school treatment assignment indicator. This yields a negative, but statistically insignificant, effect of treatment of schoolmates on infection among older girls (Appendix Table AIV). We cannot reject the hypothesis that the IV estimates of the within-school externality are the same as the probit estimates presented below.

28 186 E. MIGUEL AND M. KREMER (age and sex eligible) children attending any primary school within three kilometers, the presence of each additional thousand (age and sex eligible) pupils attending Group 1 schools located within three kilometers of a school is associated with 26 percentage points fewer moderate-to-heavy infections, and this coefficient estimate is significantly different than zero at 99 percent confidence. Each additional thousand pupils attending a Group 1 school located between three to six kilometers away is associated with 14 percentage points fewer moderate-to-heavy infections, which is smaller than the effect of pupils within three kilometers, as expected, and is significantly different than zero at 95 percent confidence (Table VII, regression 1). 36 Due to the relatively small size of the study area, we are unable to precisely estimate the impact of additional treatment school pupils farther than six kilometers away from a school, and thus cannot rule out the possibility that there were externalities at distances beyond six kilometers and possibly for the study area as a whole, in which case the estimates presented in Table VII (and discussed below) would be lower bounds on actual externality benefits. 37,38 36 We experimented with alternative measures of infection status. One such measure normalizes the egg count for each type of infection by dividing each egg count by the moderate-heavy infection threshold for that helminth, and then summing up the normalized egg counts across all four infections (hookworm, roundworm, schistosomiasis, and whipworm) to arrive at an overall infection score. The results using this measure are similar to those using the moderate-to-heavy infection indicator, although the estimated reduction in worm prevalence due to within-school externalities becomes statistically insignificant (results available upon request). 37 The use of the intention-to-treat estimation method could potentially create spurious findings of cross-school deworming externalities, since students initially in comparison schools who transfer into treatment schools in time to receive treatment are still classified as comparison pupils. However, we do not think this is a serious problem in practice since our results are nearly identical when we classify students not by their original school, but by the school they actually attended at the time of the parasitological survey (results available upon request). The relevant transfer rate between March 1998 and November 1998 is simply too small to account for the externalities we detect: only 1.6 percent of students in Groups 2 and 3 transferred into Group 1 schools during 1998, and only 1.4 percent of students in Group 1 transferred to Groups 2 or 3 (Table IV). Given that some of the Group 2 and 3 children presumably transferred too late in the school year to benefit from treatment, and that some early transfers did not receive treatment, fewer than 1 percent of comparison pupils were treated (Table III). 38 These results are largely robust to including the proportion of Group 1 pupils in the surrounding area as the explanatory variable, rather than the total number of Group 1 pupils in the surrounding area (see regressions 3 and 7 in Appendix Table AIII). The use of spatially correlated disturbance terms does not lead to substantial changes in standard errors and confidence levels (see regressions 2 and 6 in Appendix Table AIII). The school participation results in Table IX are also robust to the use of spatially correlated disturbance terms (results not shown). We examined the extent of spatial correlation across schools using Conley (1999) and Chen and Conley s (2001) semi-parametric framework, and as expected, find a positive and declining relationship between the correlation in infection rates and distance between schools, although the spatial correlation is relatively small once we condition on school-level characteristics. The crossschool externality results are also robust to controlling for initial 1998 infection levels among the sample of Group 1 pupils with both 1998 and 1999 parasitological data (see regressions 4 and 8

29 WORMS: IDENTIFYING IMPACTS 187 We estimate that moderate-to-heavy helminth infections among children in this area were 23 percentage points (standard error 7 percentage points) lower on average in early 1999 as a result of health spillovers across schools over forty percent of overall moderate-to-heavy infection rates in Group 2 schools. To see this, note that the average spillover gain is the average number of Group 1 pupils located within three kilometers divided by 1000 (N T ) 03 times the average effect of an additional 1000 Group 1 pupils located within three kilometers on infection rates (γ 03 ), plus the analogous spillover effect due to schools located between three to six kilometers away from the school (refer to equation (1)). Based on the externality estimates in Table VII, regression 1, this implies the estimated average cross-school externality reduction in moderate-to-heavy helminth infections is [γ 03 N T + γ N T ]= 36 1 [ ]/1000 = Note that deworming drugs kill worms already in the body, but the drugs do not remain in the body and do not provide immunity against future reinfection, so it is plausible that the benefit from having fewer sources of reinfection is reasonably orthogonal to current infection status. However, own treatment and local treatment intensity need not simply have an additive effect on moderate-to-heavy infections: the interaction effect will be negative if cross-school externalities alone do not typically reduce infection levels below the moderate-to-heavy infection threshold for comparison school pupils as of the date of the parasitological survey, but the interaction of own treatment and externalities often does reduce infection below the threshold for treatment school pupils. 39 We find that the average cross-school externality reduction in moderate-to-heavy infections for comparison school (Group 2) pupils is 9 percentage points, while the effect for treatment school (Group 1) pupils is considerably larger, at nearly 29 percentage points (Table VII, regression 3). As discussed below, this difference is primarily due to geohelminths externalities, since externalities for the more serious schistosomiasis infections are similar for treatment and comparison schools. The existence of cross-school health externalities implies that the difference in average outcomes between treatment and comparison schools a naïve treatment effect estimator understates the actual effects of mass deworming treatment on the treated. If externalities disappear completely after six kilometers, the true reduction in moderate-to-heavy infection rates among pupils in Group 1 schools is the sum of the average cross-school externality for comparison school pupils (9 percentage points) and the effect of being in a treatment school in early 1999 presented in Table VII, regression 1 (25 percentage in Appendix Table AIII). We can only control for initial 1998 infection levels in the subsample of Group 1 schools, since these data were not collected for the other schools. 39 More generally, the distribution of individual worm infection relative to the threshold level is also important for gauging the likely interaction effect between own treatment and the local treatment intensity.

30 188 E. MIGUEL AND M. KREMER points), for a total of 35 percentage points (the standard error is 9 percentage points, taking into account the covariance structure across coefficient estimates from Table VII, regression 3). The cross-school externality is thus over one-quarter as large as the total effect on the treated. The estimated number of moderate-to-heavy helminth infections eliminated through the program is thus (0 35) (9 817 pupils in Group 1 schools) +(0 09) ( Pupils in Group 2 and 3 schools) = 5190 infections. This is nearly one infection eliminated per treated child in Group 1 schools. Even this figure underestimates the actual total treatment effect of the program by excluding any benefits to schools more than six kilometers from treatment schools, and benefits for school-age children not enrolled in school, other community members not of school age such as the pre-primary children discussed above and people who live in villages bordering the study area, whom we did not survey. As discussed in Section 2, externalities are likely to operate over larger distances for schistosomiasis than for geohelminths. In fact, the cross-school externality effects are mainly driven by reductions in moderate-to-heavy schistosomiasis infections (Table VII, regression 4), while cross-school geohelminth externalities are negative and marginally significant within three kilometers but not significantly different than zero from three to six kilometers (regression 7). The within-school effect is driven by geohelminth infections (coefficient estimate 0 10, standard error 0.04, regression 8), while the within-school schistosomiasis externalities are negative but insignificant (regression 5). Finally, the coefficient estimates on interaction terms between treatment group and local treatment intensity are not statistically significantly different than zero for moderate-to-heavy schistosomiasis infections (Table VII, regression 6), but the interaction between treatment group and local treatment intensity from zero to three kilometers is negative and significant for moderateto-heavy geohelminth infections (regression 9). In other words, pupils in comparison and treatment schools benefit similarly from proximity to treatment schools in terms of reduced schistosomiasis infection, but treatment school pupils experience larger cross-school geohelminth externalities than comparison pupils DEWORMING TREATMENT EFFECTS ON SCHOOL PARTICIPATION This section argues that deworming increased school participation in treatment schools by at least seven percentage points, a one-quarter reduction in to- 40 For schistosomiasis, one explanation for this results is that cross-school externalities are sufficiently large to reduce infection levels below the moderate-to-heavy threshold for many pupils in both treated and comparison schools, and as a result coefficient estimates on the interaction terms are not significant.

31 WORMS: IDENTIFYING IMPACTS 189 tal school absenteeism. 41 Deworming may have improved school participation by allowing previously weak and listless children to attend school regularly or by improving children s ability to concentrate, which may have made attending school increasingly worthwhile relative to other activities, such as agricultural labor, staying at home, or fishing. As with the health impacts, deworming creates externalities in school participation both within and across schools; after accounting for externalities we estimate that overall school participation in this area likely increased by at least 0.14 years of schooling per pupil actually treated through the program. This effect is larger than would be expected from nonexperimental estimates of the correlation between worm burden and school participation, as we discuss below. Our sample consists of all pupils enrolled in school or listed in the school register during the first term in Since many pupils attend school erratically, and the distinction between an absent pupil and a dropout is often not clear from school records, it is difficult to distinguish between dropping out and long-term absenteeism; moreover, measuring pupil attendance conditional on not dropping out is unattractive since dropping out is endogenous. We therefore focus on a comprehensive measure of school participation: a pupil is considered a participant if she or he is present in school on a given day, and a nonparticipant if she or he is not in school on that day. Since school attendance records are often poorly kept, school participation was measured during unannounced school visits by NGO field workers. Schools received an average of 3.8 school participation check visits per year in 1998 and Note that since the days of medical treatment were pre-announced, and the school 41 School participation in the area is irregular, and the large effect we estimate is consistent with the hypothesis that many children are at the margin of whether or not to attend school given the cost of school fees and uniforms, low school quality, and perceived declining returns to education (Mensch and Lloyd (1997)). Further evidence that many children are at the margin of whether to attend school is provided by a program in the same region that paid for required school uniforms, increasing school participation by 15 percent (Kremer, Moulin, and Namunyu (2002)). 42 Since many pupils who were recorded as dropouts in early 1998 re-enrolled in school at some point during the 1998 or 1999 school years, we include them in the sample. However, many initial dropouts were not assigned a grade by the NGO field staff, complicating the analysis of participation rates by grade. Such pupils are assigned their own grade indicator variable in Table IX. Some pupils have missing year of birth information due to absence from school on days of questionnaire or exam administration, and certain assumptions need to be made regarding the treatment assignment status of girls with missing age information (since older girls were supposed to be excluded from treatment). Girls in treatment schools in preschool and grades 1, 2, and 3 are assumed to be eligible for treatment, while those in grades 7 and 8 are assumed not to be, since all but a small fraction of girls in these grades meet the respective age eligibility criterion. We do not know if girls with missing ages in grades 4, 5, and 6 were younger than 13 and hence were supposed to receive treatment, and therefore we drop them from the sample, eliminating 99 girls from the sample of approximately 30,000 children. An additional 119 pupils are dropped from the sample due to both missing age and sex information.

32 190 E. MIGUEL AND M. KREMER participation figures do not include attendance on these days, effects on attendance are not due to children coming to school in the hope of receiving medicine School Participation Differences across Treatment and Comparison Schools Before proceeding to formal estimation using equations (1) and (3), we first present differences in school participation across the project groups and through time. Since these do not take cross-school externalities into account, they potentially underestimate overall treatment effects. Among girls younger than thirteen years old and all boys, the difference in school participation for the five post-treatment participation observations in the first year after medical treatment is 9.3 percentage points, and this is significantly different than zero at 99 percent confidence (Table VIII). The difference is larger among boys and young girls than among the older girls (5.7 percentage points), which is consistent with the fact that a far smaller proportion of older girls actually received medical treatment (Table III). The differences in 1999 school participation for boys and younger girls are also large and significantly different than zero at 90 percent confidence for both Group 1 (1998 and 1999 treatment schools) and Group 2 (1999 treatment schools), at 5.0 and 5.5 percentage points, respectively. Average school participation rates fall during the second year of the study as children from the original sample and especially those in the older grades left school through graduation or dropping-out. One possible explanation for the smaller impact of the program on school participation in 1999 is the lower proportion of pupils taking deworming drugs compared to 1998 (Table III), which should reduce both treatment effects on the treated and externality effects. The larger participation differences between treatment and comparison schools in 1998 may also have been due to the widespread El Niño flooding in this region in early 1998, which substantially increased worm loads between early 1998 and early 1999 (to see this, compare Tables II and V). Finally, the difference may be due in part to chance: we cannot reject the hypothesis that gaps between treatment and comparison schools in 1998 and 1999 are the same. The time pattern of school participation differences is consistent with a causal effect of deworming on school participation. Figure 1 presents school participation rates from May 1998 to November 1999 for girls under thirteen and for all boys. Diamonds represent the differences in average school participation between Group 1 and Group 3 schools, and squares represent the difference between Group 2 and Group 3 schools. School participation rates for Group 1 schools are consistently higher than rates in Group 3 schools in both 1998 and 1999, and the gap stands at nearly ten percentage points by November Group 2 schools have lower school participation than Group 3 schools in 1998 when both groups were comparison schools, but begin to show

34 192 E. MIGUEL AND M. KREMER FIGURE 1. School participation rate May 1998 to November 1999 for girls under 13 years old and for all boys (difference between Group 1 and Group 3 (diamonds), and difference between Group 2 and Group 3 (squares)). a a The shaded regions are periods in which medical treatment was being provided (in March April and November 1998 to Group 1 schools, and March June and October November 1999 to Group 1 and Group 2 schools). participation gains in early Participation in Group 2 schools is substantially greater than in Group 3 schools by mid-1999 when the first round of 1999 treatment was concluded. These gains resulted primarily from a greater proportion of pupils with participation above 80 percent, although there were also substantially fewer dropouts (results not shown). The school participation gains are particularly large among the youngest pupils: in 1998 the average difference in participation between treatment and comparison groups for preschool through grade 2 was 10.0 percentage points (significantly different than zero at 99 percent confidence), while for pupils in grades 6 to 8 it was 5.9 percentage points, and in 1999 the comparable gains for Group 2 pupils were 8.5 percentage points and 2.6 percentage points, respectively. The larger impact of treatment in lower grades may partially result from higher rates of moderate-to-heavy infection among younger pupils (Table II). It is also possible that school participation is more elastic with respect to health for younger pupils; many Kenyan children drop out before reaching the upper primary grades, so older children who remain in school may be the most academically serious and determined to attend school despite illness. Untreated pupils in Group 1 (1998 treatment) had higher school participation than their counterparts in Group 2 schools who were later untreated during 1999, consistent with deworming externalities on school participation. Among girls under thirteen years old and all boys, May 1998 to March

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